Friday, March 28, 2014

By way of Mark Thoma, an absolutely brilliant paper by economist Paul Pfleiderer of Stanford University looking at how economists use and abuse models. As he points our, if you make the right assumptions (ignoring market "distortions" such as liver disease, DUIs, etc.), then it's possible to show in a rigorous model that "it is optimal for humans to be drinking all of their waking hours." I've written some more over at Medium.

Wednesday, March 26, 2014

I recently stumbled across this fascinating preprint from last year by some computer scientists and applied mathematicians. They show how the taxi system in NYC could be made roughly 40% more efficient (fewer miles driven, lots less pollution, etc) with a taxi sharing system that would help people coordinate their trips. Making it work requires data and algorithms; the 40% improvement could be achieved, in principle, while introducing no more than a 5 minute delay to any person's trip.

Looks like great idea, right in line with the spirit of using information to improve coordination. I've written a short article on the research at Medium.

Monday, March 24, 2014

Economist Chris House wonders why so many physicists are drawn to economics. It's a fair question, and I suppose it must seem strange -- perhaps irritating -- to see people interloping from a foreign field, fully convinced that they'll be able to help out even without formal economics training. Chris thinks the physicists often believe, mistakenly, that they're mathematically superior to economists, and so might be able to sort out some big problems quite easily.

Friday, March 21, 2014

In the age of the Internet, and mobile everything, we increasingly need to interact with complete strangers. We don't know them, we can't trust them, yet we'd like to enter into positive exchanges with them, to cooperate and to trade, while protecting ourselves. How can we do it?

Maybe with ROT, by which I of course mean Random Oblivious Transfer, the latest weird idea looming up in quantum cryptography. More at Medium.com.

Yahoo! Inc.’s total value is represented by the first bar. If you
subtract the value of Alibaba Group Holding Ltd. and Yahoo! Japan Corp.
you are left with Yahoo's core business -- excluding its Japanese and
Chinese investments -- and a negative valuation.
I can remember a
few examples of the efficient, all-knowing markets getting the valuation
of a company completely wrong. It doesn’t happen often, but it's kind
of amusing when it does.

Maybe Marissa Mayer isn't doing a
terrible job, but Mr. Market simply made a mistake. This chart should
make you question whether we give markets too much credit for being
efficient and intelligent.

Monday, March 17, 2014

Joseph Stiglitz is always worth reading. On the wrong side of globalization looks at the ongoing effort to surreptitiously create the Trans-Pacific Partnership, or TPP, which would "bring together 12
countries along the Pacific Rim in what would be the largest free trade
area in the world." It's euphemistically called a "free trade" bill, yet negotiations between nations have curiously been going on in secret. Why? Mostly, Stiglitz suggests, because the TPP is really an effort to find ways for corporations to arbitrage regulations and improve profits while subverting democratic policy making around the world:

...agreements like the TPP are only one aspect of a larger problem: our gross mismanagement of globalization.

Let’s tackle the history first. In general,
trade deals today are markedly different from those made in the decades
following World War II, when negotiations focused on lowering tariffs.
As tariffs came down on all sides, trade expanded, and each country
could develop the sectors in which it had strengths and as a result,
standards of living would rise. Some jobs would be lost, but new jobs
would be created.

Today, the purpose of trade agreements is
different. Tariffs around the world are already low. The focus has
shifted to “nontariff barriers,” and the most important of these — for
the corporate interests pushing agreements — are regulations. Huge
multinational corporations complain that inconsistent regulations make
business costly. But most of the regulations, even if they are
imperfect, are there for a reason: to protect workers, consumers, the
economy and the environment.

What’s more, those regulations were often put
in place by governments responding to the democratic demands of their
citizens. Trade agreements’ new boosters euphemistically claim that they
are simply after regulatory harmonization, a clean-sounding phrase that
implies an innocent plan to promote efficiency. One could, of course,
get regulatory harmonization by strengthening regulations to the highest
standards everywhere. But when corporations call for harmonization,
what they really mean is a race to the bottom.
When agreements like the TPP govern
international trade — when every country has agreed to similarly minimal
regulations — multinational corporations can return to the practices
that were common before the Clean Air and Clean Water Acts became law
(in 1970 and 1972, respectively) and before the latest financial crisis
hit. Corporations everywhere may well agree that getting rid of
regulations would be good for corporate profits. Trade negotiators might
be persuaded that these trade agreements would be good for trade and
corporate profits. But there would be some big losers — namely, the rest
of us.

These high stakes are why it is especially
risky to let trade negotiations proceed in secret. All over the world,
trade ministries are captured by corporate and financial interests. And
when negotiations are secret, there is no way that the democratic
process can exert the checks and balances required to put limits on the
negative effects of these agreements.

The secrecy might be enough to cause
significant controversy for the TPP. What we know of its particulars
only makes it more unpalatable. One of the worst is that it allows
corporations to seek restitution in an international tribunal, not only
for unjust expropriation, but also for alleged diminution of their
potential profits as a result of regulation. This is not a theoretical
problem. Philip Morris has already tried this tactic against Uruguay,
claiming that its antismoking regulations, which have won accolades from
the World Health Organization, unfairly hurt profits, violating a
bilateral trade treaty between Switzerland and Uruguay. In this sense,
recent trade agreements are reminiscent of the Opium Wars, in which
Western powers successfully demanded that China keep itself open to
opium because they saw it as vital in correcting what otherwise would be
a large trade imbalance.

Provisions already incorporated in other
trade agreements are being used elsewhere to undermine environmental and
other regulations. Developing countries pay a high price for signing on
to these provisions, but the evidence that they get more investment in
return is scant and controversial. And though these countries are the
most obvious victims, the same issue could become a problem for the
United States, as well. American corporations could conceivably create a
subsidiary in some Pacific Rim country, invest in the United States
through that subsidiary, and then take action against the United States
government — getting rights as a “foreign” company that they would not
have had as an American company. Again, this is not just a theoretical
possibility: There is already some evidence that companies are choosing
how to funnel their money into different countries on the basis of where
their legal position in relation to the government is strongest.

There are other noxious provisions. America
has been fighting to lower the cost of health care. But the TPP would
make the introduction of generic drugs more difficult, and thus raise
the price of medicines. In the poorest countries, this is not just about
moving money into corporate coffers: thousands would die unnecessarily.
Of course, those who do research have to be compensated. That’s why we
have a patent system. But the patent system is supposed to carefully
balance the benefits of intellectual protection with another worthy
goal: making access to knowledge more available. I’ve written
before about how the system has been abused by those seeking patents
for the genes that predispose women to breast cancer. The Supreme Court
ended up rejecting those patents, but not before many women suffered
unnecessarily. Trade agreements provide even more opportunities for patent abuse.

The worries mount. One way of reading the
leaked negotiation documents suggests that the TPP would make it easier
for American banks to sell risky derivatives around the world, perhaps
setting us up for the same kind of crisis that led to the Great
Recession.

In spite of all this, there are those who
passionately support the TPP and agreements like it, including many
economists. What makes this support possible is bogus, debunked economic
theory, which has remained in circulation mostly because it serves the
interests of the wealthiest.

Free trade was a central tenet of economics
in the discipline’s early years. Yes, there are winners and losers, the
theory went, but the winners can always compensate the losers, so that
free trade (or even freer trade) is a win-win. This conclusion,
unfortunately, is based on numerous assumptions, many of which are
simply wrong.

The older theories, for instance, simply
ignored risk, and assumed that workers could move seamlessly between
jobs. It was assumed that the economy was at full employment, so that
workers displaced by globalization would quickly move from
low-productivity sectors (which had thrived simply because foreign
competition was kept at bay through tariffs and other trade
restrictions) to high-productivity sectors. But when there is a high
level of unemployment, and especially when a large percentage of the
unemployed have been out of work long-term (as is the case now), there
can’t be such complacency.

Today, there are 20 million Americans who
would like a full-time job but can’t get one. Millions have stopped
looking. So there is a real risk that individuals moved from low
productivity-employment in a protected sector will end up
zero-productivity members of the vast ranks of the unemployed. This
hurts even those who keep their jobs, as higher unemployment puts
downward pressure on wages.

We can argue over why our economy isn’t
performing the way it’s supposed to — whether it’s because of a lack of
aggregate demand, or because our banks, more interested in speculation
and market manipulation than lending, are not providing adequate funds
to small and medium-size enterprises. But whatever the reasons, the
reality is that these trade agreements do risk increasing unemployment.

One of the reasons that we are in such bad
shape is that we have mismanaged globalization. Our economic policies
encourage the outsourcing of jobs: Goods produced abroad with cheap
labor can be cheaply brought back into the United States. So American
workers understand that they have to compete with those abroad, and
their bargaining power is weakened. This is one of the reasons that the
real median income of full-time male workers is lower than it was 40 years ago.

American politics today compounds these
problems. Even in the best of circumstances, the old free trade theory
said only that the winners could compensate the losers, not that they
would. And they haven’t — quite the opposite. Advocates of trade
agreements often say that for America to be competitive, not only will
wages have to be cut, but so will taxes and expenditures, especially on
programs that are of benefit to ordinary citizens. We should accept the
short-term pain, they say, because in the long run, all will benefit.
But as John Maynard Keynes famously said in another context, “in the
long run we are all dead.” In this case, there is little evidence that
the trade agreements will lead to faster or more profound growth.

Critics of the TPP are so numerous because
both the process and the theory that undergird it are bankrupt.
Opposition has blossomed not just in the United States, but also in
Asia, where the talks have stalled.

Friday, March 14, 2014

For everyone but the top 1 percent of
earners, the American economy is broken. Since the 1980s, there has been
a widening disconnect between the lives lived by ordinary Americans and
the statistics that say our prosperity is growing. Despite the setback
of the Great Recession, the U.S. economy more than doubled in size
during the last three decades while middle-class incomes and buying
power have stagnated. Great fortunes were made while many baby boomers
lost their retirement savings. Corporate profits reached record highs
while social mobility reached record lows, lagging behind other
developed countries. For too many families, the American Dream is
becoming more a historical memory than an achievable reality.

These facts don’t just highlight the issues of inequality and the
growing power of a plutocracy. They should also force us to ask a deeper
set of questions about how our economy works—and, crucially, about how
we assess and measure the very idea of economic progress.

How can it be that great wealth is created on Wall Street with
products like credit-default swaps that destroyed the wealth of ordinary
Americans—and yet we count this activity as growth? Likewise, fortunes
are made manufacturing food products that make Americans fatter, sicker,
and shorter-lived. And yet we count this as growth too—including the
massive extra costs of health care. Global warming creates more frequent
hurricanes, which destroy cities and lives. Yet the economic activity
to repair the damage ends up getting counted as growth as well.

Our economic policy discussions are nearly always focused on making
us wealthier and on generating the economic growth to accomplish that.
Great debates rage about whether to raise or lower interest rates, or
increase or decrease regulation, and our political system has been
paralyzed by a bitter ideological struggle over the budget. But there is
too little debate about what it is all for. Hardly anyone ever asks:
What kind of growth do we want? What does “wealth” mean? And what will
it do for our lives?

Thursday, March 13, 2014

High-frequency trading is controversial. More than half of
all trading now takes place this way, and there's no end in sight to
this “arms race” to ever faster speeds. Does it make sense? Is it fair, sensible, or possibly dangerous? New research suggests that HFT does bring benefits as it "synchronizes" the pricing of different related securities, making markets work better for the average investor. Curiously, HFT seems to make assets "flock" together in much the way we see birds flock or fish swim together in schools. Read more at Medium.com.

Scientists have struggled for many years to define life. What is living and what is not? Is a virus alive? What about a growing crystal? No one has been successful, and I think I agree with Ferris Jabr in the New York Times: there is no answer. There simply is no sharp dividing line between what is alive and what is not. The idea that there should be is a confusion, a prejudice, and it is all in our heads; it's not a part of reality.

Monday, March 10, 2014

Noah Smith has a new post which displays his great flexibility as a blogger. He's a fairly stern critic of modern macroeconomics, usually. This post is a more or less conscious effort to do mental gymnastics by suspending relevant sense data and seeing just how far it is possible, if one tries really hard, to offer a coherent defense of current practices in mainstream macroeconomics (read: DSGE modelling). One big positive: there was a financial crisis, and DSGE modellers deserve great credit as they have now noticed the importance of the financial system and made strides in including it (in some form at least) in their models. Another: macroeconomists, apparently, are trying to make their models simpler so they can be more useful to policy makers. I say apparently.

Because that's not what I heard at a recent conference from policy makers themselves. My latest Bloomberg column explores a little of what I heard from some of them about what they would like to see more of from macroeconomists. More realistic finance and more simplicity were certainly on their list, alongside a lot more humility, more acceptance of uncertainty, and more models based on realistic human behavior. They said they haven't seen much of this yet:

... are the top journals in macroeconomics publishing useful work? Judging from a recent conference
that included regulators from the U.S. Federal Reserve, the Bank of
England, the International Monetary Fund and the Organization for
Economic Cooperation and Development, the answer is not encouraging: Six
years after a financial crisis that exposed fundamental flaws in the
dominant economic theories and models, the profession has made little to
no progress in correcting itself.

The policy makers said that
top economics journals still aren't publishing research or providing
tools that they can apply in their work. The dominant culture favors
mathematically complex, intellectually stimulating theories over
simpler, more useful ones. "We're in for a long siege,” as one of them
put it, “during which useful economics that really works will remain out
of the top theoretical journals.” [Read more]

That last quote really struck me. Useful work will stay out of the top journals. How then can they be considered top journals? What am I missing?

At that conference, I gave a short presentation during a panel session. I (cautiously) presented my impression that one reason economists don't want to move away from their models based on rationality and equilibrium is that, in doing so, they will inevitably have to give up some of their favorite theorems and hence be unable to make statements about the possible welfare implications of policies. Taking steps toward realism will invalidate the mathematical basis of their thinking. I see that as a good thing; many economists I believe find it downright frightening.

That is my impression as an outsider, but am pleased to see that economist Peter Dorman believes something similar, a point he made in commenting on Noah Smith's post (h/t Lars Syll):

“….macroeconomists are definitely thinking about
heterogeneity.” Come on, you must surely see that one can have both
heterogeneity and representative agents. If there are 300 million agents
in an economy and you model them as two or three decision-makers, on
balance you are doing a lot more homogenizing than heterogenizing. This
matters because just about everything we know about complex systems
tells us that the density of interaction effects is central. An economy
of you, me and a few other people simply isn’t going to have the same
dynamics as an economy of millions of interacting agents. This is true
even if agent-based modeling turns out to be unproductive. It’s enough
to know that the model people are using is systematically giving bad
advice. Microfounding macro is a choice, and if the there aren’t any
good microfoundations at hand, you don’t have to do it.

“….there’s no clear alternative [to rational expectations].” The
previous paragraph applies here as well. If the only microfoundations
you can find are empirically disconfirmed, regularly and broadly, then
you may just have to postpone this microfounding business until you can
come up with better models. Beyond that, I think the core problem is
that the models are structured to permit the solution of equilibrium
conditions, and that this imposes a restrictive framework for thinking
about rationality, optimization. If the point were to model adjustment,
we could use a much looser but more empirically defensible conception of
rationality. Of course, that would also mean severing economic analysis
from welfarism: we’d have to give up trying to answer questions
like“what’s the welfare cost of this situation compared to the optimum?”
In the end, the attachment of economists, micro and macro alike, to
equilibrium models with rational agents is that they want to be able
make definitive judgments about what society should do. I prefer Keynes’
dentists: they don’t tell you whether you have an optimal dental
structure, but they can help you get the structure you tell them you
want.

“….[macro] looks like a vigorous, energetic field full of excited
young true believers and respected older figures who are still blazing
new trails.” The more accurate criticism of macro is not that it is
simply an ideological smokescreen or an unthinking herd, but that it
operates on a tilted playing field. It is openly acknowledged that the
“leading” (i.e. career-determining) journals have engaged in tendentious
selection practices for the past generation. Lots of shoddy research
(which in my book includes calibration exercises promoted as “testing”
theories) has gotten the star treatment, alongside a stream of genuinely
significant macro work. Ideologically loaded assumptions, such as those
typically used in public choice, are dropped in without any
justification. Not all macro is bad! But the problem is that (a) the bad
stuff of a certain ideological orientation gets an extra push that the
good stuff doesn’t get, and (b) there isn’t a clear process by which the
bad stuff is weeded out over time as its badness becomes evident. We
refight the same damned macro battles year after year.

Again, I think economists like to tell stories of a certain kind, stories that fit into a certain framework they find familiar, a framework that links up to all the nice (?) welfare theorems they learned as students. The only problem is that these theorems only apply to a fictitious world that is not at all like our world. So we have the top journals filled with useless theory. Wonderful.

Friday, March 7, 2014

Anyone who has read this blog consistently knows that I've written on and off about an important developing body of work showing how algorithms -- closely linked to Google's PageRank algorithm -- could be used to greatly increase transparency surrounding issues of systemic risk. The systemic risk linked to any one bank or even to any single financial transaction could be made apparent to everyone; call it "radical transparency." Coupled with other mechanisms, such transparency could provide a route to making the system safer on is own, through normal economic self organization. The idea, in essence, is to use computation to give everyone in the market the information they need to make better choices.

I've written about this here, here and most recently here. I've just put a kind of short summary article of all this up at Medium.com. But I'd also like to just quote some of the nice discussion from the most recent paper of Stefan Thurner and Sebastian Poledna. I think they describe the idea with beautiful clarity; so here's a whole big section. After describing various ideas currently under consideration for dealing with Too Big to Fail and systemic risk more generally, they note that..

No
matter how well intended these developments might be, they miss the
central point about the nature of SR, and might not be suitable to
improve stability of the financial system in a sustainable way. SR is
tightly related to the network structure of
financial assets and liabilities in
a financial system. Management of SR is essentially a matter of
re-structuring financial networks such that the probability of
cascading failure is reduced, or ideally eliminated.

Credit
risk is the risk that a borrower will default on a given debt by
failing to make the full pre-specified re-payments. It is usually
seen as a risk that emerges between two counterparties once they
engage in a financial transaction. The lender is the sole bearer of
credit risk, and figures the likelihood of failed repayments into a
risk premium. Lenders usually charge higher interest rates to
borrowers that are more likely to default (risk-based pricing).
Credit risk is relatively well understood, and can be mitigated
through a number methods and techniques [18].
The Basle accords provide an extensive framework dealing foremost
with the mitigation of credit risk [19–21].

When
two counterparties are part of a financial system, for example as
nodes in a financial network, the situation changes, and their
transaction may affect the financial system as a whole. The lender no
more is the sole bearer of credit risk, nor does credit risk depend
on the financial conditions of the borrower alone. The impact of a
default of the borrower is no longer limited to the lender, but it
may affect the other creditors of the lender (who also lend to the
same borrower) as well as their creditors, and so on. Similarly, the
lender is not only vulnerable to a default of the borrower but also
to defaults from all debtors of that borrower as well as their
debtors, etc. In financial networks credit risk loses the local
character between two counterparties, and becomes systemic.

SR
is the risk that the financial system as a whole or a large fraction
of it can no longer perform its function as a credit provider and
collapses. SR is a result of the network nature of financial
transactions and liabilities in the financial system. It unfolds as
secondary cascades of credit defaults, triggered by credit defaults
between individual counterparties. These cascades can potentially
wipe out the financial system by a de-leveraging cascade [22–29].
It is obvious that lenders have a strong incentive to mitigate credit
risk. In the case of SR the situation is less clear, since the
loss-bearers will in general not be directly involved in those
transactions that trigger systemic damage. It is not obvious which
players in the financial system have a true interest to mitigate SR.
Management of SR is foremost in the public interest.

It
is important to note that SR spreads by lending. If a systemically
risky node lends to a systemically non-risky one, the later inherits
SR from the risky node, since if the non-risky borrower should (for
whatever reason) not repay the loan, the risky node would trigger
systemic damage. In this sense SR spreads from the risky through
lending.

SR
is predominantly a network property of liability networks. Different
financial network topologies will have different probabilities for
systemic collapse, given the link density and the financial
conditions of nodes being the same. The management of SR becomes a
technical problem of managing the network topology of financial
networks. The goal is to do this in a way that does neither reduce
the credit provision capacity, nor the transaction volume of the
financial system. Data on the topology of credit networks is
available to many central banks. Several studies on historical data
show typical scale-free connectivity patterns in liability networks
[30–35], including overnight markets [36], and financial flows
[37]. As a network property, SR can be quantified by using
networkmetrics [38, 39]. In particular a relative risk measure
(DebtRank) can be assigned to all nodes in a financial network that
specifies the fraction of SR they contribute to the system
(institution- or node-specific SR) [39]. As shown later, it is
natural to extend the notion of node-specific SR to individual
liabilities between two counterparties
(liability-specific SR), and to individual transactions
(transaction-specific SR).

The
central idea of this paper is to introduce an incentive structure in
form of a transaction tax that dynamically structures liability
networks such that SR is minimized. Since every transaction in a
financial network has an impact on the overall SR of a system, we
suggest a transaction
tax on all transactions between any two market participants that
increase the SR of the entire system. The size of the tax is
proportional to the SR contribution of the particular transaction.
Market participants looking for credit will try to avoid this tax by
looking for credit opportunities that do not increase SR and are thus
tax free. As a consequence the network arranges toward a topology
that, in combination with the financial conditions of individual
institutions, will lead to a defacto
elimination of SR,
meaning that cascading failures can no longer occur. In the spirit of
risk-based pricing as it is used for credit risk, here we propose a
systemic risk premium.
It was shown in [39] that SR can be drastically reduced by reducing
borrowing from
systemically risky
nodes. This is achieved by distributing SR evenly over the network
and by preventing the emergence of systemically super-risky nodes.
The mechanism works in a self-organized way: risky nodes reduce their
SR because they are blocked from lending, non-risky nodes become more
systemically risky through their lending. A SR premium encourages
borrowers to borrow from safer lenders (since the borrower pays the
tax). Further, lenders have an incentive to become systemically safe
so that no (or only little) SRT is added to their loan offers, and
they can offer competitive rates. Since mitigation of SR is foremost
in the public interest we propose to charge a systemic risk tax as a
margin on every financial transaction that increases global SR.

Of course it will take lots of further thought to bring this into a practical form. But big ideas always start out small.

Wednesday, March 5, 2014

I've started what is called a collection over at Medium.com. The collection's name is the same as this blog. To follow content added to the collection, go here and click the link. This IS an experiment, so I'm not sure where it will go, but this is how we learn, we hope. At Medium, anyone can submit a story to a collection and the collection editor acts as the curator. In time I hope it won't be just me writing there.

A "just so" story is one that gives a nice comforting but ultimately fantastic explanation for some puzzling and unexplained thing. Rudyard Kipling of course made the idea famous in his book of that name. The Leopard's spots, in his story, were originally painted on by an Ethiopian, after that Ethiopian had first painted himself black.

Modern economists have picked up the ball and now, with their sophisticated Dynamic Stochastic General Equilibrium models, tell similar just so stories to explain (after the fact, of course) how economies work. It's all comes down to a lot of infinite forward thinking, rational optimization and equilibrium. I do wonder in fact if there is anything that could conceivable happen in an economy that DSGE modellers wouldn't be able to "explain" after sufficient work. Indeed, that would be an interesting exercise for DSGE lovers: can you make a short list of economic happenings that would clearly be inconsistent with your theories?

On a related matter, I think there is something very fishy about economists' defense of DSGE models as being useful for "telling stories." I've heard this excuse several times recently. No, they may not find much empirical support, and no, they're not much good for prediction, and no again, no one on Wall St. uses them in making practical investment decisions. BUT STILL -- these things are really very useful because they let us tell stories about how the economy works. That to me smells rotten.

I've written an essay on these "just so" stories over at Medium.com. I'm experimenting with writing over there a little, and will continue exploring themes relevant to The Physics of Finance. I'll always put a link here so anyone interested can go through.

I wrote recently in Bloomberg about a really cool proposal to introduce a new kind of tax on financial transactions. The tax would be specifically linked to how much systemic risk a transaction -- say a loan from one bank to another -- creates. It's easy to roll your eyes when you hear about transaction taxes, thinking A. it will never happen and B. it might not do much good even if it did. There are real reasons to believe that a transaction tax might damage market liquidity. But the thing I'm writing about here is VERY different.

This is a tax institutions DON'T HAVE TO PAY. Institutions that work hard to borrow and lend in a way that doesn't increase risk to the overall financial system (by piling up debt on particular institutions, for example) would end up paying no tax. The idea is to bring systemic risk into the pricing system so institutions have an incentive to avoid it. In so doing, you provide a mechanism for the entire financial network to reconfigure itself to have lower systemic risk. The paper I'm writing about proposes a concrete method to do this, although it would in practice require giving central banks more information on financial transactions of many kinds.

This is the kind of really creative thinking we need a lot more of. Read more here.

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This blogexplores the potential for the transformation of economics and finance through the inspiration of physics and the other natural sciences. If traditional economics has emphasized self-regulation and market equilibrium, the new perspective emphasizes the myriad positive feed backs that often drive markets away from equilibrium and cause tumultuous crashes and other crises. Read more about the idea.

Who am I?

Physicist and science writer. I was formerly an editor with the international science journal Nature and also the magazine New Scientist. I am the author of three earlier books, and have written extensively for publications including Nature, Science, the New York Times, Wired and the Harvard Business Review. I currently write monthly columns for Nature Physics and for Bloomberg Views.